The Role of Artificial Intelligence in Ensuring Transparency and Accountability in Corporate Social Responsibility Initiatives

Corporate Social Responsibility (CSR) has shifted from voluntary philanthropy to a core governance domain in which stakeholders demand verifiable evidence of social and environmental performance. Yet CSR reporting remains plagued by greenwashing, inconsistent metrics, and assurance practices that are largely point-in-time and self-interested. This paper examines how artificial intelligence (AI) can strengthen transparency and accountability in CSR initiatives. Drawing on a structured review of peer-reviewed literature and authoritative institutional reports published between 2011 and 2024, the paper develops a conceptual framework that maps four AI capabilities—natural language processing, machine-learning anomaly detection, blockchain-enabled distributed ledgers, and conversational AI—to four CSR mechanisms: dis-closure verification, real-time monitoring, traceability-based assurance, and participatory stake-holder engagement. The analysis argues that these mechanisms collectively reduce information asymmetry, harmonise divergent ESG ratings, and operationalise the EU Corporate Sustainability Reporting Directive (CSRD) and the Artificial Intelligence Act. The paper also identifies critical limitations, including the “black-box accountability paradox”, algorithmic bias, data-quality constraints, and a widening digital divide between multinational enterprises and small and medium-sized firms. It concludes that AI is a necessary but insufficient enabler: realising its transformative potential requires combined progress on data standards, third-party model audits, regulatory sandboxes, and meaningful stakeholder participation in AI governance.